1,274 research outputs found

    A survey on software coupling relations and tools

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    Context Coupling relations reflect the dependencies between software entities and can be used to assess the quality of a program. For this reason, a vast amount of them has been developed, together with tools to compute their related metrics. However, this makes the coupling measures suitable for a given application challenging to find. Goals The first objective of this work is to provide a classification of the different kinds of coupling relations, together with the metrics to measure them. The second consists in presenting an overview of the tools proposed until now by the software engineering academic community to extract these metrics. Method This work constitutes a systematic literature review in software engineering. To retrieve the referenced publications, publicly available scientific research databases were used. These sources were queried using keywords inherent to software coupling. We included publications from the period 2002 to 2017 and highly cited earlier publications. A snowballing technique was used to retrieve further related material. Results Four groups of coupling relations were found: structural, dynamic, semantic and logical. A fifth set of coupling relations includes approaches too recent to be considered an independent group and measures developed for specific environments. The investigation also retrieved tools that extract the metrics belonging to each coupling group. Conclusion This study shows the directions followed by the research on software coupling: e.g., developing metrics for specific environments. Concerning the metric tools, three trends have emerged in recent years: use of visualization techniques, extensibility and scalability. Finally, some coupling metrics applications were presented (e.g., code smell detection), indicating possible future research directions. Public preprint [https://doi.org/10.5281/zenodo.2002001]

    Analysing the Contribution of Coupling Metrics for the Development and Management of Process Architectures

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    Currently, the development and modeling of enterprise architectures is an intensively discussed topic in both science and practice. Process architectures represent a core element in recent enterprise architecture frameworks. With process models being a central means for communicating and documenting the process architectures, both their quality and understandability are decisive. However, the concept of process model quality is still not fully understood. The recent development has highlighted the role of coupling in models. Coupling is expected to represent an important dimension of quality for conceptual models. Still, this perspective is hardly understood and its definition vague. Therefore, this work collects diverse coupling interpretations in the field of process modelling and integrates them to a common and precise definition. Once introduced and formally specified, the metrics serve as a basis for a discussion on coupling and on how the future development in respect to coupling could look like. The main findings are that currently metrics evaluate either the documentation of the process architecture regarding its understandability or they contribute to the individual applications of process architectures. These findings support practitioners selecting metrics for a particular task and scientists to identify research gaps for further development

    Identification of microservices from monolithic applications through topic modelling

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    Microservices emerged as one of the most popular architectural patterns in the recent years given the increased need to scale, grow and flexibilize software projects accompanied by the growth in cloud computing and DevOps. Many software applications are being submitted to a process of migration from its monolithic architecture to a more modular, scalable and flexible architecture of microservices. This process is slow and, depending on the project’s complexity, it may take months or even years to complete. This paper proposes a new approach on microservice identification by resorting to topic modelling in order to identify services according to domain terms. This approach in combination with clustering techniques produces a set of services based on the original software. The proposed methodology is implemented as an open-source tool for exploration of monolithic architectures and identification of microservices. A quantitative analysis using the state of the art metrics on independence of functionality and modularity of services was conducted on 200 open-source projects collected from GitHub. Cohesion at message and domain level metrics’ showed medians of roughly 0.6. Interfaces per service exhibited a median of 1.5 with a compact interquartile range. Structural and conceptual modularity revealed medians of 0.2 and 0.4 respectively. Our first results are positive demonstrating beneficial identification of services due to overall metrics’ resultsNational Funds through the Portuguese funding agency, FCT - Fundação para a Ciência e a Tecnologia within project UIDB/50014/202

    Access to recorded interviews: A research agenda

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    Recorded interviews form a rich basis for scholarly inquiry. Examples include oral histories, community memory projects, and interviews conducted for broadcast media. Emerging technologies offer the potential to radically transform the way in which recorded interviews are made accessible, but this vision will demand substantial investments from a broad range of research communities. This article reviews the present state of practice for making recorded interviews available and the state-of-the-art for key component technologies. A large number of important research issues are identified, and from that set of issues, a coherent research agenda is proposed

    Methodbook: Recommending Move Method Refactorings via Relational Topic Models

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    SEMO: a framework for customer social networks analysis based on semantics

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    The increasing importance of the Internet in most domains has brought about a paradigm change in consumer relations. The influence of Social Networks has entered the Customer Relationship Management domain under the coined term CRM 2.0. In this context, the need to understand and classify the interactions of customers by means of new platforms has emerged as a challenge for both researchers and professionals world-wide. This is the perfect scenario for the use of SEMO, a platform for Customer Social Networks Analysis based on Semantics and emotion mining. The platform benefits from both semantic annotation and classification and text analysis, relying on techniques from the Natural Language Processing domain. The results of the evaluation of the experimental implementation of SEMO reveal a promising and viable platform from a technical perspective.This work is supported by the Spanish Ministry of Industry, Tourism, and Commerce under the EUREKA project SITIO (TSI-020400-2009-148), SONAR2 (TSI-020100-2008-665) and GO2 (TSI-020400-2009-127)Publicad

    Altmetrics as a research specialty (Dimensions, 2005-2018)

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    Se analiza la bibliografía científica sobre altmétricas publicada entre 2005 y 2018. La estructura general de su paisaje intelectual se caracteriza en términos de concentraciones temáticas de referencias cocitadas. Se aplican análisis de cocitación de revistas y de cocitación de autores. Con una consulta a la base bibliográfica Dimensions se extraen 8.145 documentos de todo tipo y 56.936 referencias citadas que integran el conjunto de datos inicial con el que se acomete el análisis. Se han generado redes Pathfinder usando CiteSpace para representar las revistas y los autores dominantes en la especialidad. La estructura temática de la especialidad se identifica mediante análisis de clusters de autores cocitados y análisis semánticos latentes. La investigación sobre “open knowledge”, “altmetric collection”, “web indicator”, “assessing research”, “researchgate score”, “open data citation advantage”, “google scholar autor citation”, “share data”, “academic tweet”, “mendeley readership count” y “social media metric”, aparecen como líneas de investigación actuales. Se aportan varios indicadores estadísticos para destacar las revistas y autores claves en la especialidad
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